tbuckley/cabot-search huggingface dataset:
Multi-faceted intervention to improve management of antibiotics for children presenting to primary care with acute cough and respiratory tract infection (CHICO): efficient cluster randomised controlled trial
Authors: Peter S Blair, Grace Young, Clare Clement, P Dixon, Penny Seume, Jenny Ingram, Jodi Taylor, Christie Cabral, Patricia J Lucas, Elizabeth Beech, Jeremy Horwood, Martin Gulliford, Nick A Francis, Sam Creavin, Janet A Lane, Scott Bevan, Alastair D Hay
Journal: BMJ (2023)

To assess whether an easy-to-use multifaceted intervention for children presenting to primary care with respiratory tract infections would reduce antibiotic dispensing, without increasing hospital admissions for respiratory tract infection.
Risk Factors of Progression in Low-tumor Burden Follicular Lymphoma Initially Managed by Watch and Wait in the Era of PET and Rituximab
Authors: Cyrielle Rodier, Lukshe Kanagaratnam, David Morland, Adélie Herbin, Amandine Durand, Adrien Chauchet, Sylvain Choquet, Philippe Colin, René Olivier Casasnovas, Eric Deconinck, François Godard, Alain Delmer, Cédric Rossi, Eric Durot
Journal: HemaSphere (2023)

Patients (pts) with asymptomatic low-burden follicular lymphoma (FL) are usually observed at diagnosis. Time to lymphoma treatment (TLT) initiation can however be very heterogeneous and risk factors of progression are poorly studied. Our study evaluated 201 pts with grade 1-3a low-tumor burden FL diagnosed in four French centers between 2010 and 2020 and managed by a watch and wait strategy in real-life settings. After a median follow-up of 4.8 years, the median TLT was 4.2 years (95% confidence interval, 3.1-5.5). On multivariate analysis, elevated lactate dehydrogenase (hazard ratio [HR] = 2.2; P = 0.02), more than 4 nodal areas involved (HR = 1.7; P = 0.02) and more than 1 extranodal involvement (HR = 2.7; P = 0.01) were identified as independent predictors of TLT. The median TLT was 5.8 years for pts with no risk factor, 2.4 years for 1 risk factor, and 1.3 years for >1 risk factors (P < 0.01). In a subanalysis of 75 pts staged with positron emission tomography-computed tomography (PET-CT), total metabolic tumor volume (TMTV) ≥14 cm3 and standardized Dmax (reflecting tumor dissemination) >0.32 m-1 were also associated with shorter TLT (HR = 3.4; P = 0.004 and HR = 2.4; P = 0.007, respectively). In multivariate models combining PET-CT parameters and clinical variables, TMTV remained independent predictor of shorter TLT. These simple parameters could help to identify FL patients initially observed at higher risk of early progression. The role of PET-CT (extranodal sites and PET metrics) in low-burden FL appears promising and warrants further assessment in large cohorts.
A systematic review of neurophysiological sensing for the assessment of acute pain
Authors: Raul Fernandez Rojas, Nicholas Brown, Gordon Waddington, Roland Goecke
Journal: npj Digital Medicine (2023)

Abstract Pain is a complex and personal experience that presents diverse measurement challenges. Different sensing technologies can be used as a surrogate measure of pain to overcome these challenges. The objective of this review is to summarise and synthesise the published literature to: (a) identify relevant non-invasive physiological sensing technologies that can be used for the assessment of human pain, (b) describe the analytical tools used in artificial intelligence (AI) to decode pain data collected from sensing technologies, and (c) describe the main implications in the application of these technologies. A literature search was conducted in July 2022 to query PubMed, Web of Sciences, and Scopus. Papers published between January 2013 and July 2022 are considered. Forty-eight studies are included in this literature review. Two main sensing technologies (neurological and physiological) are identified in the literature. The sensing technologies and their modality (unimodal or multimodal) are presented. The literature provided numerous examples of how different analytical tools in AI have been applied to decode pain. This review identifies different non-invasive sensing technologies, their analytical tools, and the implications for their use. There are significant opportunities to leverage multimodal sensing and deep learning to improve accuracy of pain monitoring systems. This review also identifies the need for analyses and datasets that explore the inclusion of neural and physiological information together. Finally, challenges and opportunities for designing better systems for pain assessment are also presented.
Secretory MPP3 reinforce myeloid differentiation trajectory and amplify myeloid cell production
Authors: Yoon-A Kang, Hyojung Paik, Si Yi Zhang, Jonathan J. Chen, Oakley C. Olson, Carl A. Mitchell, Amelie Collins, James W. Swann, Matthew R. Warr, Rong Fan, Emmanuelle Passegué
Journal: The Journal of Experimental Medicine (2023)

Hematopoietic stem cells (HSC) and downstream lineage-biased multipotent progenitors (MPP) tailor blood production and control myelopoiesis on demand. Recent lineage tracing analyses revealed MPPs to be major functional contributors to steady-state hematopoiesis. However, we still lack a precise resolution of myeloid differentiation trajectories and cellular heterogeneity in the MPP compartment. Here, we found that myeloid-biased MPP3 are functionally and molecularly heterogeneous, with a distinct subset of myeloid-primed secretory cells with high endoplasmic reticulum (ER) volume and FcγR expression. We show that FcγR+/ERhigh MPP3 are a transitional population serving as a reservoir for rapid production of granulocyte/macrophage progenitors (GMP), which directly amplify myelopoiesis through inflammation-triggered secretion of cytokines in the local bone marrow (BM) microenvironment. Our results identify a novel regulatory function for a secretory MPP3 subset that controls myeloid differentiation through lineage-priming and cytokine production and acts as a self-reinforcing amplification compartment in inflammatory stress and disease conditions.
Interfering with Interferons: A Critical Mechanism for Critical COVID-19 Pneumonia
Authors: Helen C. Su, Huie Jing, Yu Zhang, Jean-Laurent Casanova
Journal: Annual Review of Immunology (2023)

Infection with SARS-CoV-2 results in clinical outcomes ranging from silent or benign infection in most individuals to critical pneumonia and death in a few. Genetic studies in patients have established that critical cases can result from inborn errors of TLR3- or TLR7-dependent type I interferon immunity, or from preexisting autoantibodies neutralizing primarily IFN-α and/or IFN-ω. These findings are consistent with virological studies showing that multiple SARS-CoV-2 proteins interfere with pathways of induction of, or response to, type I interferons. They are also congruent with cellular studies and mouse models that found that type I interferons can limit SARS-CoV-2 replication in vitro and in vivo, while their absence or diminution unleashes viral growth. Collectively, these findings point to insufficient type I interferon during the first days of infection as a general mechanism underlying critical COVID-19 pneumonia, with implications for treatment and directions for future research.
Ibrutinib sensitizes CLL cells to venetoclax by interrupting TLR9-induced CD40 upregulation and protein translation
Authors: Karoline Kielbassa, Marco V. Haselager, Danique J. C. Bax, Bianca F. van Driel, Julie Dubois, Mark-David Levin, Sabina Kersting, Rebecka Svanberg, Carsten U. Niemann, Arnon P. Kater, Eric Eldering
Journal: Leukemia (2023)

Abstract Chronic lymphocytic leukemia (CLL) cells upregulate Bcl-2 proteins within the lymph node (LN) microenvironment. Signaling via B-cell receptor, Toll-like receptors and CD40 collectively reduce sensitivity to the BCL-2 inhibitor venetoclax. Time-limited treatment with venetoclax plus the BTK-inhibitor ibrutinib results in deep remissions, but how this combination affects LN-related signaling is not yet completely clear. Therefore, samples obtained from the HOVON141/VISION phase 2 clinical trial were used to analyze this. Two cycles of lead-in ibrutinib monotherapy resulted in decreased protein expression of Bcl-2 proteins in circulating CLL cells. Strikingly, at this timepoint CD40-induced venetoclax resistance was strongly attenuated, as was expression of CD40. Since CD40 signaling occurs within the CLL LN, we tested various LN-related signals that could affect CD40 signaling. While BCR stimulation had only a minor effect, TLR9 stimulation via CpG led to significantly increased CD40 expression and importantly, reverted the effects of ibrutinib treatment on venetoclax sensitivity by inducing overall protein translation. Together, these findings identify a novel effect of ibrutinib: interruption of TLR9-induced CD40 upregulation and translation of pro-survival proteins. This mechanism may potentially further inhibit priming of CLL cells in the LN microenvironment for venetoclax resistance.
Modeling T Cell Fate
Authors: Rob J. De Boer, Andrew J. Yates
Journal: Annual Review of Immunology (2023)

Many of the pathways that underlie the diversification of naive T cells into effector and memory subsets, and the maintenance of these populations, remain controversial. In recent years a variety of experimental tools have been developed that allow us to follow the fates of cells and their descendants. In this review we describe how mathematical models provide a natural language for describing the growth, loss, and differentiation of cell populations. By encoding mechanistic descriptions of cell behavior, models can help us interpret these new datasets and reveal the rules underpinning T cell fate decisions, both at steady state and during immune responses.
The EGR3 regulome of infant KMT2A-r acute lymphoblastic leukemia identifies differential expression of B-lineage genes predictive for outcome
Authors: Marius Külp, Patrizia Larghero, Julia Alten, Gunnar Cario, Cornelia Eckert, Aurélie Caye-Eude, Hélène Cavé, Tessa Schmachtel, Michela Bardini, Giovanni Cazzaniga, Paola De Lorenzo, Maria Grazia Valsecchi, Halvard Bonig, Claus Meyer, Michael A. Rieger, Rolf Marschalek
Journal: Leukemia (2023)

Abstract KMT2A -rearranged acute lymphoblastic infant leukemia ( KMT2A -r iALL) is associated with outsize risk of relapse and relapse mortality. We previously reported strong upregulation of the immediate early gene EGR3 in KMT2A :: AFF1 iALL at relapse; now we provide analyses of the EGR3 regulome, which we assessed through binding and expression target analysis of an EGR3-overexpressing t(4;11) cell culture model. Our data identify EGR3 as a regulator of early B-lineage commitment. Principal component analysis of 50 KMT2A -r iALL patients at diagnosis and 18 at relapse provided strictly dichotomous separation of patients based on the expression of four B-lineage genes. Absence of B-lineage gene expression translates to more than two-fold poorer long-term event-free survival. In conclusion, our study presents four B-lineage genes with prognostic significance, suitable for gene expression-based risk stratification of KMT2A -r iALL patients.
SRSF2-P95H decreases JAK/STAT signaling in hematopoietic cells and delays myelofibrosis development in mice
Authors: Christophe Willekens, Lucie Laplane, Tracy Dagher, Camelia Benlabiod, Nicolas Papadopoulos, Catherine Lacout, Philippe Rameau, Cyril Catelain, Alexia Alfaro, Valérie Edmond, Nicolas Signolle, Valentine Marchand, Nathalie Droin, Remco Hoogenboezem, Rebekka K. Schneider, Alex Penson, Omar Abdel-Wahab, Stephane Giraudier, Florence Pasquier, Caroline Marty, Isabelle Plo, Jean-Luc Villeval, Stefan N. Constantinescu, Françoise Porteu, William Vainchenker, Eric Solary
Journal: Leukemia (2023)
Molecular mimicry and cancer vaccine development
Authors: Maria Tagliamonte, Beatrice Cavalluzzo, Angela Mauriello, Concetta Ragone, Franco M. Buonaguro, Maria Lina Tornesello, Luigi Buonaguro
Journal: Molecular Cancer (2023)

Abstract Background The development of cancer immunotherapeutic strategies relies on the identification and validation of optimal target tumor antigens, which should be tumor-specific as well as able to elicit a swift and potent anti-tumor immune response. The vast majority of such strategies are based on tumor associated antigens (TAAs) which are shared wild type cellular self-epitopes highly expressed on tumor cells. Indeed, TAAs can be used to develop off-the-shelf cancer vaccines appropriate to all patients affected by the same malignancy. However, given that they may be also presented by HLAs on the surface of non-malignant cells, they may be possibly affected by immunological tolerance or elicit autoimmune responses. Main body In order to overcome such limitations, analogue peptides with improved antigenicity and immunogenicity able to elicit a cross-reactive T cell response are needed. To this aim, non-self-antigens derived from microorganisms (MoAs) may be of great benefit.
The proposed EU Directives for AI liability leave worrying gaps likely to impact medical AI
Authors: Mindy Nunez Duffourc, Sara Gerke
Journal: npj Digital Medicine (2023)

Two newly proposed Directives impact liability for artificial intelligence in the EU: a Product Liability Directive (PLD) and an AI Liability Directive (AILD). While these proposed Directives provide some uniform liability rules for AI-caused harm, they fail to fully accomplish the EU's goal of providing clarity and uniformity for liability for injuries caused by AI-driven goods and services. Instead, the Directives leave potential liability gaps for injuries caused by some black-box medical AI systems, which use opaque and complex reasoning to provide medical decisions and/or recommendations. Patients may not be able to successfully sue manufacturers or healthcare providers for some injuries caused by these black-box medical AI systems under either EU Member States' strict or fault-based liability laws. Since the proposed Directives fail to address these potential liability gaps, manufacturers and healthcare providers may have difficulty predicting liability risks associated with creating and/or using some potentially beneficial black-box medical AI systems.
Soluble ORF2 protein enhances HEV replication and induces long-lasting antibody response and protective immunity in vivo
Authors: Philipp Ralfs, Brantley Holland, Eduardo Salinas, Bill Bremer, Minghang Wang, Jingting Zhu, Charuta Ambardekar, Heather Blasczyk, Christopher M. Walker, Zongdi Feng, Arash Grakoui
Journal: Hepatology (2023)

Background and Aims: The HEV is a small positive–sense RNA virus that encodes a cytoplasmic form of the capsid protein (ORF2c), essential for virion structure, and a secreted glycosylated form (ORF2s) that accumulates at high titer in serum and can mask neutralizing epitopes. We explored the contribution of ORF2s to HEV replication and its role in generating antibodies against ORF2 in a nonhuman primate model. Approach and Results: We used a recombinant HEV genotype 3 variant that does not express ORF2s due to the introduction of stop codons (ORF2s mut ). Rhesus macaques (RMs) were given intrahepatic injections of infectious wildtype HEV (ORF2s wt ) RNA or a variant lacking ORF2s expression (ORF2s mut ). The replication of the ORF2s mut virus was delayed by ~2 weeks compared with ORF2s wt , and peak titers were nearly tenfold lower. Reversions of the 3 mutations that blocked ORF2s expression were not detected in the ORF2s mut genomes, indicating genetic stability. However, serum antibodies against ORF2 were transiently detected in RMs infected with ORF2s mut , whereas they were long-lasting in RMs infected with ORF2s wt . Moreover, RMs infected with ORF2s mut were more susceptible to reinfection, as evidenced by the viral RNA detected in fecal samples and the expansion of HEV-specific CD8 + T cells. Conclusions: These findings indicate that ORF2s may be dispensable for viral replication in vivo but is required for long-lived antibody-mediated responses that protect against HEV re-exposure.
Comparing scientific abstracts generated by ChatGPT to real abstracts with detectors and blinded human reviewers
Authors: Catherine A. Gao, Frederick M. Howard, Nikolay S. Markov, Emma C. Dyer, Siddhi Ramesh, Yuan Luo, Alexander T. Pearson
Journal: npj Digital Medicine (2023)

Abstract Large language models such as ChatGPT can produce increasingly realistic text, with unknown information on the accuracy and integrity of using these models in scientific writing. We gathered fifth research abstracts from five high-impact factor medical journals and asked ChatGPT to generate research abstracts based on their titles and journals. Most generated abstracts were detected using an AI output detector, ‘GPT-2 Output Detector’, with % ‘fake’ scores (higher meaning more likely to be generated) of median [interquartile range] of 99.98% ‘fake’ [12.73%, 99.98%] compared with median 0.02% [IQR 0.02%, 0.09%] for the original abstracts. The AUROC of the AI output detector was 0.94. Generated abstracts scored lower than original abstracts when run through a plagiarism detector website and iThenticate (higher scores meaning more matching text found). When given a mixture of original and general abstracts, blinded human reviewers correctly identified 68% of generated abstracts as being generated by ChatGPT, but incorrectly identified 14% of original abstracts as being generated. Reviewers indicated that it was surprisingly difficult to differentiate between the two, though abstracts they suspected were generated were vaguer and more formulaic. ChatGPT writes believable scientific abstracts, though with completely generated data. Depending on publisher-specific guidelines, AI output detectors may serve as an editorial tool to help maintain scientific standards. The boundaries of ethical and acceptable use of large language models to help scientific writing are still being discussed, and different journals and conferences are adopting varying policies.
Use of noninvasive scores to predict hepatic steatosis: Flaws and caveats
Authors: Leon A. Adams, Phillip J. Schulte, Alina M. Allen
Journal: Hepatology (2023)

1Medical School, University of Western Australia, Nedlands, Western Australia, Australia 2Department of Hepatology, Sir Charles Gairdner Hospital, Nedlands, Western Australia, Australia 3Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota, USA 4Department of Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minnesota, USA Abbreviations: BMI, body mass index; FLI, fatty liver index; GGT, gamma-glutamyl transferase; MRS, magnetic resonance spectroscopy; TG, triglyceride; WC, waist circumference. Correspondence Leon A. Adams, Medical School, University of Western Australia, QEII Medical Campus, M503, Verdun St, Nedlands, WA 6009, Australia. Email: [email protected]
AI-assisted prediction of differential response to antidepressant classes using electronic health records
Authors: Yi-han Sheu, Colin Magdamo, Matthew Miller, Sudeshna Das, Deborah Blacker, Jordan W. Smoller
Journal: npj Digital Medicine (2023)

Antidepressant selection is largely a trial-and-error process. We used electronic health record (EHR) data and artificial intelligence (AI) to predict response to four antidepressants classes (SSRI, SNRI, bupropion, and mirtazapine) 4 to 12 weeks after antidepressant initiation. The final data set comprised 17,556 patients. Predictors were derived from both structured and unstructured EHR data and models accounted for features predictive of treatment selection to minimize confounding by indication. Outcome labels were derived through expert chart review and AI-automated imputation. Regularized generalized linear model (GLM), random forest, gradient boosting machine (GBM), and deep neural network (DNN) models were trained and their performance compared. Predictor importance scores were derived using SHapley Additive exPlanations (SHAP). All models demonstrated similarly good prediction performance (AUROCs ≥ 0.70, AUPRCs ≥ 0.68). The models can estimate differential treatment response probabilities both between patients and between antidepressant classes for the same patient. In addition, patient-specific factors driving response probabilities for each antidepressant class can be generated. We show that antidepressant response can be accurately predicted from real-world EHR data with AI modeling, and our approach could inform further development of clinical decision support systems for more effective treatment selection.
A multicenter time series study on pollen exposure and <scp>COVID</scp>‐19 infection in five cities in China
Authors: Xiaozhe Yang, Jing Zhang, Yutong Sima, Jinming Zhao, Xiangdong Wang, Luo Zhang
Journal: Allergy (2023)

Data S1: Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.
Clinical Connections
Journal: Arthritis & Rheumatology (2023)

There remain unanswered questions and an incomplete understanding of the T cell composition of the affected rheumatoid ar thritis (RA) joint.With new technologies, such studies, including the T cell receptor (TCR) repertoire, have become much easier.In the current study, Turcinov et al assessed T cells in small joint synovium at the time of RA diagnosis.
Editorial Expression of Concern: Let-7d suppresses growth, metastasis, and tumor macrophage infiltration in renal cell carcinoma by targeting COL3A1 and CCL7
Authors: Boxing Su, Wei Zhao, Bentao Shi, Zhongyuan Zhang, Xi Yu, Feng Xie, Zhongqiang Guo, Xiaoyu Zhang, Jin Liu, Qi Shen, Jinghua Wang, Xuesong Li, Zhiqian Zhang, Liqun Zhou
Journal: Molecular Cancer (2023)
Strategic Design of Conquering Hypoxia in Tumor for Advanced Photodynamic Therapy
Authors: Cheng Zhang, Xiaoming Hu, Long Jin, Lisheng Lin, Hongxin Lin, Zhen Yang, Wei Huang
Journal: Advanced Healthcare Materials (2023)

Photodynamic therapy (PDT), with its advantages of high targeting, minimally invasive, and low toxicity side effects, has been widely used in the clinical therapy of various tumors, especially superficial tumors. However, the tumor microenvironment (TME) presents hypoxia due to the low oxygen (O2 ) supply caused by abnormal vascularization in neoplastic tissues and high O2 consumption induced by the rapid proliferation of tumor cells. The efficacy of oxygen-consumping PDT can be hampered by a hypoxic TME. To address this problem, researchers have been developing advanced nanoplatforms and strategies to enhance the therapeutic effect of PDT in tumor treatment. This review summarizes recent advanced PDT therapeutic strategies to against the hypoxic TME, thus enhancing PDT efficacy, including increasing O2 content in TME through delivering O2 to the tumors and in situ generations of O2 ; decreasing the O2 consumption during PDT by design of type I photosensitizers. Moreover, recent synergistically combined therapy of PDT and other therapeutic methods such as chemotherapy, photothermal therapy, immunotherapy, and gas therapy is accounted for by addressing the challenging problems of mono PDT in hypoxic environments, including tumor resistance, proliferation, and metastasis. Finally, perspectives of the opportunities and challenges of PDT in future clinical research and translations are provided.
MORC proteins regulate transcription factor binding by mediating chromatin compaction in active chromatin regions
Authors: Zhenhui Zhong, Yan Xue, C. Jake Harris, Ming Wang, Zheng Li, Yunqing Ke, Mukun Liu, Jessica Zhou, Yasaman Jami-Alahmadi, Suhua Feng, James A. Wohlschlegel, Steven E. Jacobsen
Journal: Genome biology (2023)

The microrchidia (MORC) proteins are a family of evolutionarily conserved GHKL-type ATPases involved in chromatin compaction and gene silencing. Arabidopsis MORC proteins act in the RNA-directed DNA methylation (RdDM) pathway, where they act as molecular tethers to ensure the efficient establishment of RdDM and de novo gene silencing. However, MORC proteins also have RdDM-independent functions although their underlying mechanisms are unknown.